---
tags:
- generated_from_trainer
model-index:
- name: codellama-7b-humaneval-java-fim
  results: []
library_name: peft
---

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# codellama-7b-humaneval-java-fim

This model was trained from scratch on an [this](https://huggingface.co./datasets/sarthak247/humaneval-java-fixed) dataset for FIM task.
It achieves the following results on the evaluation set:
- Loss: 0.6155

## Model description

Codellama-7b model trained for FIM on Java code dataset.

## Intended uses & limitations

Bleh

## Training and evaluation data

Dataset mentioned above

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6594        | 0.05  | 100  | 0.6927          |
| 0.6701        | 0.1   | 200  | 0.6784          |
| 0.6329        | 0.15  | 300  | 0.6690          |
| 0.6361        | 0.2   | 400  | 0.6629          |
| 0.5964        | 0.25  | 500  | 0.6545          |
| 0.6247        | 0.3   | 600  | 0.6461          |
| 0.6146        | 0.35  | 700  | 0.6407          |
| 0.5892        | 0.4   | 800  | 0.6364          |
| 0.5916        | 0.45  | 900  | 0.6308          |
| 0.6069        | 0.5   | 1000 | 0.6267          |
| 0.5804        | 0.55  | 1100 | 0.6242          |
| 0.5793        | 0.6   | 1200 | 0.6212          |
| 0.5836        | 0.65  | 1300 | 0.6195          |
| 0.5839        | 0.7   | 1400 | 0.6174          |
| 0.597         | 0.75  | 1500 | 0.6162          |
| 0.6042        | 0.8   | 1600 | 0.6158          |
| 0.5777        | 0.85  | 1700 | 0.6155          |
| 0.5683        | 0.9   | 1800 | 0.6155          |
| 0.5613        | 0.95  | 1900 | 0.6155          |
| 0.5597        | 1.0   | 2000 | 0.6155          |


### Framework versions

- PEFT 0.5.0
- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.14.1